SciELO - Scientific Electronic Library Online

 
vol.19 issue2Growth and Metabolism: Regulation and the Insulin Pathway from a Fruit Fly's Viewpoint author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


TIP. Revista especializada en ciencias químico-biológicas

Print version ISSN 1405-888X

Abstract

MONROY-ATA, Arcadio  and  PENA-BECERRIL, Juan Carlos. On the nature of evolution: an explicative model. TIP [online]. 2016, vol.19, n.2, pp.127-132. ISSN 1405-888X.  https://doi.org/10.1016/j.recqb.2016.06.006.

For years, links between entropy and information of a system have been proposed, but their changes in time and in their probabilistic structural states have not been proved in a robust model as a unique process. This document demonstrates that increasement in entropy and information of a system are the two paths for changes in its configuration status. Biological evolution also has a trend toward information accumulation and complexity. In this approach, the aim of this article is to answer the question: What is the driven force of biological evolution? For this, an analogy between the evolution of a living system and the transmission of a message in time was made, both in the middle of environmental noise and stochasticity. A mathematical model, initially developed by Norbert Wiener, was employed to show the dynamics of the amount of information in a message, using a time series and the Brownian motion as statistical frame. Léon Brillouin's mathematical definition of information and Claude Shannon's entropy equation were employed, both are similar, in order to know changes in the two physical properties. The proposed model includes time and configurational probabilities of the system and it is suggested that entropy can be considered as missing information, according to Arieh Ben-Naim. In addition, a graphic shows that information accumulation can be the driven force of both processes: evolution (gain in information and complexity), and increase in entropy (missing information and restrictions loss). Finally, a living system can be defined as a dynamic set of information coded in a reservoir of genetic, epigenetic and ontogenic programs, in the middle of environmental noise and stochasticity, which points toward an increase in fitness and functionality.

Keywords : biological evolution; entropy; information; living systems; messages; noise.

        · abstract in Spanish     · text in English     · English ( pdf )